There are no effective treatments for pancreatic ductal adenocarcinma (PDAC), accounting for the abysmal statistic of fewer than 4% of patients surviving 5 years beyond diagnosis. With the incidence of PDAC on the rise it is increasingly urgent that we expand our knowledge of the mechanisms that promote the development, progression, metastasis and drug resistance of PDAC, to pave the way for the development of new therapeutic modalities. There is compelling evidence that in addition to the defects in oncogenic and tumor suppressor pathways intrinsic to the malignant tumor cells, extrinsic signals from the tumor microenvironment (TME) also play critical roles in PDAC. Inflammatory cells, stromal cells, extracellular matrix (ECM), and proteases are amongst the components of the TME that promote tumorigenesis and contribute to drug resistance. Recent studies indicate that disrupting extrinsic signals (including sonic hedgehog, lysyl-oxidase, fibroblast activation protein (FAP) or CD40) can inhibit the development and/or progression of tumors in various tumor types including PDAC. Although these studies targeted distinct pathways, they revealed that alterations in the content and/or organization of the extracellular matrix in the tumor microenvironment may be a common mechanism underlying their impact on tumorigenesis. FAP is a cell surface serine protease selectively expressed on carcinoma associated stromal cells (including PDAC) that we have shown plays a critical role in remodeling the ECM in the TME of lung and colon cancer models. In the proposed studies, using a genetic approach we will extend these studies to two genetically engineered mouse models of PDAC to test the hypothesis that FAP promotes the development and/or progression of PDAC and define the mechanisms involved. To determine the translational potential of targeting FAP, we will also determine whether pharmacologic inhibition of FAP inhibits PDAC progression as a monotherapy or enhances efficacy of chemotherapy in these genetically engineered mouse models of PDAC.